Reliability and validity of Healthy Fitness Measurement Scale Version1.0 (HFMS V1.0) in Chinese elderly people.

PURPOSE: We examined the reliability and validity of the Healthy Fitness Measurement Scale Version 1.0 (HFMS V1.0) specifically on elderly people in China. METHODS: We carried out a cross-sectional study in December 2020 and enrolled 800 elderly people through stratified sampling technique, including 777 valid samples (with a mean age of 71.81 ± 8.36 years), of which 382 cases (49.2%) were women. The level of healthy fitness was measured using the HFMS V1.0. The Cronbach's alpha coefficient, split-half reliability, test-retest reliability, convergent and discriminant validity, exploratory factor and confirmatory factor were calculated for assessing the reliability and validity of HFMS V1.0. RESULTS: HFMS V1.0 consists of 8 dimensions and 38 items. The scale had acceptable reliability (Cronbach's alpha = 0.920, split-half = 0.946, test-retest = 0.878). Exploratory factor analysis showed KMO value =0.927, and uncovered 10 factors with the cumulative contribution rate of 65.71% and all factor loads over 0.40. The item distribution was consistent with the initial expectation of the scale. The confirmatory factor analysis indicated good fit: CMIN/DF = 2.796, RMSEA = 0.048, IFI =0.914, TLI = 0.902, CFI = 0.913. CONCLUSION: HFMS V1.0 was shown to have acceptable reliability and validity indices for this sample. Collectively, HFMS V1.0 is reliable and efficient to measure the healthy fitness of elderly people. It is recommended to use it among the elderly in other Chinese cities in the future to ensure uniformity and objectivity. This scale can be carried out to evaluate of the effectiveness of public health measures in improving the healthy fitness level of the elderly and optimizing public health policies.

Prognostic value of miR-21 in gliomas: comprehensive study based on meta-analysis and TCGA dataset validation.

Recent studies have highlighted the value of microRNA-21 (miR-21) as a prognostic biomarker in gliomas. However, the role of miR-21 in predicting prognosis remains controversial. We performed a comprehensive study based upon a meta-analysis and The Cancer Genome Atlas (TCGA) glioma dataset validation to clarify the prognostic significance of miR-21 in glioma patients. In this study, we searched Embase, PubMed, Web of science, CNKI, SinoMed, and Wanfang databases for records up to May 2018. Relevant data were extracted to assess the correlation between miR-21 expression and survival in glioma patients. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to describe association strength. We further used multivariate Cox regression analysis to assess miR-21 expression in the TCGA glioma dataset to validate the relationship between miR-21 expression and survival. Nine studies were included in the meta-analysis. Among them, eight studies provided data on overall survival (OS) with a pooled HR of 1.91 (95% CI: 1.34, 2.73), indicating that higher expression of miR-21 was significantly associated with worse OS in glioma patients; for the other study, which provided data on progression-free survival (PFS), no statistically significant HR was reported for PFS in the glioma patients (HR = 1.23, 95% CI: 0.41, 3.72). A multivariate Cox regression analysis of the miR-21 expression in the TCGA glioma dataset revealed that overexpression of miR-21 was a potential independent prognostic biomarker of poorer OS (HR = 1.27, 95% CI: 1.01, 1.59) and poorer PFS (HR = 1.46, 95% CI: 1.17, 1.82). Our findings suggest that higher expression of miR-21 is correlated with poorer glioma prognosis.

An integrated model of clinical information and gene expression for prediction of survival in ovarian cancer patients.

Accumulating evidence shows that clinical factors alone are not adequate for predicting the survival of patients with ovarian cancer (OvCa), and many genes have been found to be associated with OvCa prognosis. The objective of this study was to develop a model that integrates clinical information and a gene signature to predict the survival durations of patients diagnosed with OvCa. We constructed mRNA and microRNA expression profiles and gathered the corresponding clinical data of 552 OvCa patients and 8 normal controls from The Cancer Genome Atlas. Using univariate Cox regression followed by a permutation test, elastic net-regulated Cox regression, and ridge regression, we generated a prognosis index consisting of 2 clinical variables, 7 protective mRNAs, 12 risky mRNAs, and 1 protective microRNA. The area under the curve of the receiver operating characteristic of the integrated clinical-and-gene model was 0.756, larger than that of the clinical-alone model (0.686) or the gene-alone model (0.703). OvCa patients in the high-risk group had a significantly shorter overall survival time compared with patients in the low-risk group (hazard ratio = 8.374, 95% confidence interval = 4.444-15.780, P = 4.90 × 10(-11), by the Wald test). The reliability of the gene signature was confirmed by a public external data set from the Gene Expression Omnibus. Our conclusions that we have identified an integrated clinical-and-gene model superior to the traditional clinical-alone model in ascertaining the survival prognosis of patients with OvCa. Our findings may prove valuable for improving the clinical management of OvCa.